import sys
import numpy as np
import pandas as pd
import seaborn as sns
sns.set_theme()
results_folder = 'mmvec_major_taxa_2'
results_base_name = 'latent_dim_3_input_prior_1.00_output_prior_1.00_beta1_0.90_beta2_0.95'
table = pd.read_table(results_folder + '/' + results_base_name + '_ranks.txt', index_col=0)
table.head()
| Propionibacteriaceae | Staphylococcus caprae or capitis | Staphylococcus epidermidis | Staphylococcus hominis | Other Staphylococci | Polyomavirus HPyV6 | Polyomavirus HPyV7 | Merkel Cell Polyomavirus | Malasseziaceae | Corynebacteriaceae | Micrococcaceae | Other families | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| featureid | ||||||||||||
| X940001 | 0.111823 | 0.006616 | 0.050163 | -0.001373 | 0.099477 | 0.048717 | -0.015278 | 0.082663 | -0.016479 | 0.391788 | 0.167430 | 0.036258 |
| X940002 | -0.037990 | -0.158498 | -0.256362 | -0.062324 | -0.022124 | -0.070099 | -0.090522 | -0.089765 | -0.051773 | -0.057602 | -0.087969 | -0.121828 |
| X940005 | -0.035200 | -0.181835 | -0.301041 | -0.328792 | 0.202456 | 0.600453 | 0.238876 | 0.140972 | 0.017801 | 0.009918 | 0.071340 | -0.009364 |
| X940007 | 0.445166 | 0.335722 | 0.224301 | 0.512379 | 0.381924 | 0.168751 | 0.260878 | 0.300112 | 0.413439 | 0.399129 | 0.329138 | 0.312755 |
| X940010 | 0.302998 | -0.218579 | 0.748987 | 0.499472 | 0.354388 | 0.560653 | 1.057405 | 0.859181 | -0.107463 | 0.440688 | 0.758574 | 0.595320 |
table['Selected'] = np.isin(table.index,
['X940203', 'X940589', 'X940625', 'X940925', 'X940936', 'X942191',
'X942237', 'X950023', 'X950028', 'X950056', 'X950157', 'X950173',
'X950193', 'X950225', 'X950228', 'X950233', 'X950254', 'X950396',
'X950485', 'X950584', 'X950661', 'X950999', 'X960035', 'X960242',
'X960306', 'X960421', 'X960463', 'X960465', 'X960712', 'X960726',
'X960934', 'X961553', 'X961686', 'X970018', 'X970091', 'X970092',
'X970232', 'X970283', 'X970327', 'X970342', 'X970633', 'X970680']
)
table.sort_values('Selected', inplace=True)
sns.relplot(
table,
y='Propionibacteriaceae', x='Staphylococcus epidermidis', hue='Selected'
)
<seaborn.axisgrid.FacetGrid at 0x7f946274a490>
sns.pairplot(table, hue='Selected')
<seaborn.axisgrid.PairGrid at 0x7f9462548790>
for i in table.columns[:-1]:
sns.displot(table, x=i, hue='Selected', multiple='stack')